{"title":"GoldPhish:使用图像进行基于内容的网络钓鱼分析","authors":"M. Dunlop, S. Groat, David Shelly","doi":"10.1109/ICIMP.2010.24","DOIUrl":null,"url":null,"abstract":"Phishing attacks continue to plague users as attackers develop new ways to fool users into submitting personal information to fraudulent sites. Many schemes claim to protect against phishing sites. Unfortunately, most do not protect against zero-day phishing sites. Those schemes that do allege to provide zero-day protection, often incorrectly label both phishing and legitimate sites. We propose a scheme that protects against zero-day phishing attacks with high accuracy. Our approach captures an image of a page, uses optical character recognition to convert the image to text, then leverages the Google PageRank algorithm to help render a decision on the validity of the site. After testing our tool on 100 legitimate sites and 100 phishing sites, we accurately reported 100% of legitimate sites and 98% of phishing sites.","PeriodicalId":314947,"journal":{"name":"2010 Fifth International Conference on Internet Monitoring and Protection","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"156","resultStr":"{\"title\":\"GoldPhish: Using Images for Content-Based Phishing Analysis\",\"authors\":\"M. Dunlop, S. Groat, David Shelly\",\"doi\":\"10.1109/ICIMP.2010.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phishing attacks continue to plague users as attackers develop new ways to fool users into submitting personal information to fraudulent sites. Many schemes claim to protect against phishing sites. Unfortunately, most do not protect against zero-day phishing sites. Those schemes that do allege to provide zero-day protection, often incorrectly label both phishing and legitimate sites. We propose a scheme that protects against zero-day phishing attacks with high accuracy. Our approach captures an image of a page, uses optical character recognition to convert the image to text, then leverages the Google PageRank algorithm to help render a decision on the validity of the site. After testing our tool on 100 legitimate sites and 100 phishing sites, we accurately reported 100% of legitimate sites and 98% of phishing sites.\",\"PeriodicalId\":314947,\"journal\":{\"name\":\"2010 Fifth International Conference on Internet Monitoring and Protection\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"156\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Fifth International Conference on Internet Monitoring and Protection\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIMP.2010.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Fifth International Conference on Internet Monitoring and Protection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIMP.2010.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GoldPhish: Using Images for Content-Based Phishing Analysis
Phishing attacks continue to plague users as attackers develop new ways to fool users into submitting personal information to fraudulent sites. Many schemes claim to protect against phishing sites. Unfortunately, most do not protect against zero-day phishing sites. Those schemes that do allege to provide zero-day protection, often incorrectly label both phishing and legitimate sites. We propose a scheme that protects against zero-day phishing attacks with high accuracy. Our approach captures an image of a page, uses optical character recognition to convert the image to text, then leverages the Google PageRank algorithm to help render a decision on the validity of the site. After testing our tool on 100 legitimate sites and 100 phishing sites, we accurately reported 100% of legitimate sites and 98% of phishing sites.